Estimating deer density and abundance using spatial mark–resight models with camera trap data

Globally, many wild deer populations are actively studied or managed for conservation, hunting, or damage mitigation purposes. These studies require reliable estimates of population state parameters, such as density or abundance, with a level of precision that is fit for purpose. Such estimates can be difficult to attain for many populations that occur in situations that are poorly suited to common survey methods. We evaluated the utility of combining camera trap survey data, in which a small proportion of the sample is individually recognizable using natural markings, with spatial mark–resight (SMR) models to estimate deer density in a variety of situations. We surveyed 13 deer populations comprising four deer species (Cervus unicolor, C. timorensis, C. elaphus, Dama dama) at nine widely separated sites, and used Bayesian SMR models to estimate population densities and abundances. Twelve surveys provided sufficient data for analysis and seven produced density estimates with coefficients of variation (CVs) ≤ 0.25. Estimated densities ranged from 0.3 to 24.6 deer km−2. Camera trap surveys and SMR models provided a powerful and flexible approach for estimating deer densities in populations in which many detections were not individually identifiable, and they should provide useful density estimates under a wide range of conditions that are not amenable to more widely used methods. In the absence of specific local information on deer detectability and movement patterns, we recommend that at least 30 cameras be spaced at 500–1,000 m and set for 90 days. This approach could also be applied to large mammals other than deer

Estimating deer density and abundance using spatial mark–resight models with camera trap data

Globally, many wild deer populations are actively studied or managed for conservation, hunting, or damage mitigation purposes. These studies require reliable estimates of population state parameters, such as density or abundance, with a level of precision that is fit for purpose. Such estimates can be difficult to attain for many populations that occur in situations that are poorly suited to common survey methods. We evaluated the utility of combining camera trap survey data, in which a small proportion of the sample is individually recognizable using natural markings, with spatial mark–resight (SMR) models to estimate deer density in a variety of situations. We surveyed 13 deer populations comprising four deer species (Cervus unicolor, C. timorensis, C. elaphus, Dama dama) at nine widely separated sites, and used Bayesian SMR models to estimate population densities and abundances. Twelve surveys provided sufficient data for analysis and seven produced density estimates with coefficients of variation (CVs) ≤ 0.25. Estimated densities ranged from 0.3 to 24.6 deer km−2. Camera trap surveys and SMR models provided a powerful and flexible approach for estimating deer densities in populations in which many detections were not individually identifiable, and they should provide useful density estimates under a wide range of conditions that are not amenable to more widely used methods. In the absence of specific local information on deer detectability and movement patterns, we recommend that at least 30 cameras be spaced at 500–1,000 m and set for 90 days. This approach could also be applied to large mammals other than deer

Hybridisation rates, population structure, and dispersal of sambar deer (Cervus unicolor) and rusa deer (Cervus timorensis) in south-eastern Australia

Context. Introduced populations of sambar deer (Cervus unicolor) and rusa deer (Cervus timorensis) are present across south-eastern Australia and are subject to local population control to alleviate their negative impacts. For management to be effective, identification of dispersal capability and management units is necessary. These species also readily hybridise, so additional investigation of hybridisation rates across their distributions is necessary to understand the interactions between the two species. Aims. Measure the hybridisation rate of sambar and rusa deer, assess broad-scale population structure present within both species and identify distinct management units for future population control, and measure the likely dispersal capability of both species. Methods. In total, 198 sambar deer, 189 rusa deer, and three suspected hybrid samples were collected across Victoria and New South Wales (NSW). After sequencing and filtering, 14 099 polymorphic single-nucleotide polymorphism (SNP) markers were retained for analysis. Hybridisation rates were assessed before the data were split by species to identify population structure, diversity indices, and dispersal distances. Key results. Across the entire dataset, 17 hybrids were detected. Broad-scale population structure was evident in sambar deer, but not among the sites where rusa deer were sampled. Analysis of dispersal ability showed that a majority of deer movement occurred within 20 km in both species, suggesting limited dispersal. Conclusions. Distinct management units of sambar deer can be identified from the dataset, allowing independent population control. Although broad-scale population structure was not evident in the rusa deer populations, dispersal limits identified suggest that rusa deer sites sampled in this study could be managed separately. Sambar × rusa deer hybrids are present in both Victoria and NSW and can be difficult to detect on the basis of morphology alone. Implications. Genetic analysis can identify broad-scale management units necessary for population control, and estimates of dispersal capability can assist in delineating management units where broad-scale population structure may not be apparent. The negative impacts associated with hybridisation require further investigation to determine whether removal of hybrids should be considered a priority management aim. © 2023 The Author(s) (or their employer(s)). Published by CSIRO Publishing

Effectiveness and costs of helicopter-based shooting of deer

Context: Helicopter-based shooting has been widely used to harvest deer or control overabundant populations in Australasia, but the effectiveness and cost of this method as a deer control tool has seldom been evaluated.Aims: We evaluated the effectiveness and costs of helicopter-based shooting of fallow deer (Dama dama) and chital deer (Axis axis) in eastern Australia by quantifying (1) reductions in density, (2) the relationship between numbers killed per hour and deer density (i.e. the functional response), (3) the costs of control and (4) the effort–outcome and cost–outcome relationships.Methods: We evaluated the costs and effectiveness of 12 aerial shooting operations aiming to reduce fallow deer (n = 8) or chital deer (n = 4) population densities at nine sites in eastern Australia. Sites were characterised by fragmented woodland, and all but one operation aimed to reduce grazing competition with livestock. We used pre-control population density estimates and operational monitoring data to estimate the costs and outcomes of each operation. We combined data from all operations to estimate the relationship between shooting effort and population reduction, as well as costs associated with different levels of effort.Key results: Population reductions for operations ranged from 5% to 75% for fallow deer, and from 48% to 88% for chital deer. The greatest population reductions occurred when effort per unit area was greatest, and the largest reductions in deer density occurred when shooting was conducted in consecutive years. The functional response of hourly kills to deer density was best described by a modified Ivlev model, with the asymptotic kill rate estimated to be 50 deer per hour. There was no support for the existence of a prey refuge, that is, a threshold population density below which no deer could be shot. Helicopter charter was the primary cost of helicopter-based shooting programs, followed by labour; firearm and ammunition costs were relatively minor.Conclusions: Helicopter-based shooting can rapidly reduce deer populations over large geographic areas, but the magnitude of the reduction depends on the effort (hours of shooting) per deer per km2.Implications: Aerial shooting operations should include a pre-control population survey so that (1) measurable objectives can be established, (2) the likely level of effort and cost required for objectives to be met can be estimated and planned for, and (3) the realised population reduction can be estimated